Technical Field
[0001] The embodiments discussed herein relate to an authentication apparatus, an authentication
program, and an authentication method configured to perform personal authentication
using biometric information.
Background Art
[0002] The human body includes biometric information that may identify an individual, some
of which is used as information for identifying and authenticating an individual.
For example, it is known that there are fingerprint, eye retina and iris, face, blood
vessel, DNA (Deoxyribo Nucleic Acid) or the like, as biometric information available
for authentication.
[0003] With the recent development of biometric authentication technology, a variety of
apparatuses have been provided which recognize such characteristics of living body
as a part of the human body, and perform personal authentication. Biometric authentication
is performed by comparing the biometric information collected at the time of registration
(registered template) with the biometric information obtained at the time of authentication.
[0004] In order to improve the precision of the authentication based on biometric information,
it is desirable to obtain biometric information with a certain precision each time
authentication is performed. However, the user to be authenticated does not always
take a proper posture when authentication is being performed. Accordingly, there has
been proposed a biometric authentication apparatus which guides biometric information
to a proper position in order to obtain biometric information which may be compared
with a registered template. For example, a biometric authentication apparatus using
a vein of a palm detects displacement of the palm, and guides the palm to a position
overlapping with the registered template (see PTL 1, for example).
Citation List
Patent Literature
[0005] PTL 1: Japanese Laid-open Patent Publication No.
2008-71158
Summary of Invention
Technical Problem
[0006] However, guiding the living body to a proper posture frequently, or each time authentication
is performed, may result in an evaluation by the user that the biometric authentication
apparatus is not user-friendly. Particularly, around the boundary of whether guidance
of the living body to a proper posture is needed or not, the user may have an experience
such that, although the user recognizes that the living body is taking a proper posture,
the living body is guided to a different proper posture from that of the user's recognition,
or the living body is not guided to a proper posture although the user doubts if the
living body is taking the proper posture. Such an experience makes it difficult for
the user to recognize a truly proper posture. In addition, a biometric authentication
apparatus providing such an experience is not convenient for a user, and thus it is
desired to reduce the guidance frequency around the boundary of whether guidance of
the living body to a proper posture is needed or not.
[0007] It is an object of the invention, which has been made in view of the foregoing, to
provide an authentication apparatus, an authentication program, and an authentication
method which may extend tolerance of the posture of the living body.
Solution to Problem
[0008] In order to solve the above-mentioned problem, an authentication apparatus includes
a surface information correcting unit and an authentication unit. The surface information
correcting unit corrects surface information on a living body surface extracted from
image information obtained by photographing the living body. The authentication unit
performs biometric authentication using the corrected surface information.
[0009] Additionally, in order to solve the above-mentioned problem, an authentication program
causing a computer to perform personal authentication using characteristics of living
body, causes the computer to perform a procedure of correcting surface information
on a living body surface extracted from image information obtained by photographing
the living body, and performing biometric authentication using the corrected surface
information.
[0010] Additionally, in order to solve the above-mentioned problem, an authentication method
performed by a computer to perform personal authentication using characteristics of
living body corrects surface information on the living body surface extracted from
the image information obtained by photographing the living body, and performs biometric
authentication using the corrected surface information.
Advantageous Effects of Invention
[0011] According to the authentication apparatus, the authentication program, and the authentication
method described above, the tolerance of posture of the living body may be extended.
[0012] The foregoing and other objects, features, and advantages of the invention will be
apparent by the following explanation in association with attached drawings depicting
preferred embodiments as examples of the invention.
Brief Description of Drawings
[0013]
[FIG. 1] FIG. 1 illustrates a configuration of an authentication apparatus of a first
embodiment.
[FIG. 2] FIG. 2 illustrates a configuration of an authentication system of a second
embodiment.
[FIG. 3] FIG. 3 illustrates a configuration of an authentication apparatus of the
second embodiment.
[FIG. 4] FIG. 4 illustrates an exemplary hardware configuration of the authentication
apparatus of the second embodiment.
[FIG. 5] FIG. 5 illustrates a configuration of a sensor unit of the second embodiment.
[FIG. 6] FIG. 6 is a flow chart of an authentication procedure of the second embodiment.
[FIG. 7] FIG. 7 is a flow chart of a surface information extraction procedure of the
second embodiment.
[FIG. 8] FIG. 8 illustrates an evaluation unit of surface information of the second
embodiment.
[FIG. 9] FIG. 9 illustrates normalization of luminance distribution of the second
embodiment.
[FIG. 10] FIG. 10 illustrates examples of surface information extraction of the second
embodiment.
[FIG. 11] FIG. 11 illustrates a variation of the evaluation unit of surface information
of the second embodiment.
[FIG. 12] FIG. 12 is a flow chart of a surface information analysis procedure of the
second embodiment.
[FIG. 13] FIG. 13 illustrates examples of surface information analysis of the second
embodiment.
[FIG. 14] FIG. 14 is a flow chart of a surface information correcting procedure of
the second embodiment.
[FIG. 15] FIG. 15 is a flow chart of a surface reflection removal procedure of the
second embodiment.
[FIG. 16] FIG. 16 illustrates surface reflection removal from the luminance distribution
of the second embodiment.
[FIG. 17] FIG. 17 illustrates an example of surface reflection removal process of
the second embodiment.
[FIG. 18] FIG. 18 is a flow chart of an unaccepted information acquisition procedure
of the second embodiment.
[FIG. 19] FIG. 19 illustrates an example of unaccepted biometric information of the
second embodiment.
[FIG. 20] FIG. 20 illustrates examples of unaccepted image of the second embodiment.
[FIG. 21] FIG. 21 illustrates an example of unaccepted environment information of
the second embodiment.
[FIG. 22] FIG. 22 illustrates examples of photographing environment image of the second
embodiment.
[FIG. 23] FIG. 23 is a flow chart of a guidance method selection procedure of the
second embodiment.
[FIG. 24] FIG. 24 illustrates an exemplary guidance information database of the second
embodiment.
[FIG. 25] FIG. 25 illustrates an exemplary guidance presentation screen of the second
embodiment.
[FIG. 26] FIG. 26 is a flow chart of a guidance method selection procedure of a third
embodiment.
[FIG. 27] FIG. 27 illustrates a configuration of an authentication apparatus of a
fourth embodiment.
[FIG. 28] FIG. 28 is a flow chart of a surface information correcting procedure of
the fourth embodiment.
[FIG. 29] FIG. 29 is a flow chart of a palm luminance model generating procedure of
the fourth embodiment.
[FIG. 30] FIG. 30 illustrates an example of surface information correcting procedure
of the fourth embodiment.
[FIG. 31] FIG. 31 illustrates luminance graphs of the fourth embodiment, as well as
states of the luminance corrected image in which surface reflection and high frequencies
are removed from the luminance graph.
Description of Embodiments
[0014] In the following, embodiments will be described referring to the drawings.
[First Embodiment]
[0015] First, an authentication apparatus of a first embodiment will be described referring
to FIG. 1. FIG. 1 illustrates a configuration of an authentication apparatus of the
first embodiment.
[0016] An authentication apparatus 1 is an apparatus which uses a living body to perform
identity authentication. The living body used by the authentication apparatus 1 for
identity authentication is a vein of a palm. The authentication apparatus 1 performs
identity authentication by comparing and matching the image information obtained by
a sensor unit photographing the palm with a preliminarily registered template.
[0017] The sensor unit, including an image sensor, photographs a target living body, generates
image information of the living body, and outputs it to the authentication apparatus
1. The image information, being image data of the living body (including, for example,
location information and luminance information), is generated with a predetermined
image format. The template is data preliminarily collected from the living body to
be used for matching of the living body.
[0018] The authentication apparatus 1 includes a surface information extraction unit 2,
a surface information analysis unit 3, a surface information correcting unit 4, and
an authentication unit 5. The surface information extraction unit 2 extracts, from
the image information obtained by photographing the palm (living body), surface information
that is used for evaluating concavity/convexity of the palm surface (living body surface).
The surface information is information that allows the concavity/convexity of the
living body surface to be evaluated, luminance information, for example. The surface
information analysis unit 3 analyzes, from the surface information, concavity/convexity
of the palm surface.
[0019] The surface information correcting unit 4 corrects the concavity/convexity of the
palm surface for the surface information. For example, the surface information correcting
unit 4 performs correction to smooth the concavity/convexity of the palm surface for
the surface information. The authentication unit 5 performs biometric authentication
using the corrected surface information.
[0020] When the surface information correcting unit 4 is not able to perform correction,
or when the result of correction is not able to be used for authentication by the
authentication unit 5, the authentication apparatus 1 newly obtains image information
of the palm. In this occasion, the authentication apparatus 1 performs notification
to guide the palm to a proper posture in order to obtain image information in which
the palm takes a proper posture. The authenticatee (user) receives the notification
and adjusts the posture of the palm.
[0021] Accordingly, through the correction performed by the surface information correcting
unit 4, there will be an increase in opportunity to perform biometric authentication
using the surface information corrected by the authentication unit 5, otherwise there
will be a decrease in opportunity for the authentication apparatus 1 to perform notification
to guide the authenticatee's palm to a proper posture. Particularly, the authentication
apparatus 1 is capable of reducing the guidance frequency around the boundary of whether
guidance of the living body to a proper posture is needed or not.
[0022] Generally, biometric information to be used in biometric authentication is obtained
from a living body and thus unstable due to the influence of biological activities
of the living body. In other words, biometric information is not always constant but
may vary within a certain range. Specifically, biometric information is influenced
by breathing of the living body, strain or relaxation of muscles, expansion or relaxation
of blood vessels, or the like. Although the authenticatee tries to stay still, the
biometric information is influenced by biological activities described above, and
involuntarily exhibits a slight variation.
[0023] In addition, the biometric information is influenced not only by biological activities,
but also by environmental changes when obtaining biometric information. The environment
when obtaining biometric information varies each time and thus it is not constant.
For example, environmental light when obtaining biometric information varies depending
on the weather or time zone under influence of outdoor light, and also varies indoor
depending on the cycle of turning on the room light such as fluorescent lamps or movement
of people around.
[0024] Biometric information is sometimes considered unsuitable for use in authentication
due to such a slight variation of biometric information or environmental changes.
The authentication apparatus 1 reduces such instability of biometric information or
influence of environmental changes by correcting biometric information. The authentication
apparatus 1 then reduces the opportunity of performing notification that guides the
living body to a proper posture.
[0025] Next, a more specific description will be provided using a second embodiment.
[Second Embodiment]
[0026] FIG. 2 illustrates a configuration of an authentication system of the second embodiment.
Although a system is illustrated as the second embodiment in which an authentication
system 10 performs authentication using a vein of a palm, it is not limited thereto
and is also applicable to a system that performs authentication using other characteristic
detection sites of the living body.
[0027] The authentication system 10 is a system that recognizes characteristics of living
body to identify and authenticate an individual, which is available when logging on
the information system or performing entrance and exit management. The authentication
system 10 is configured to include an authentication apparatus 20, an authentication
apparatus 30, an authentication apparatus 40, an authentication server 50, and a network
51.
[0028] The authentication apparatus 20, the authentication apparatus 30, and the authentication
apparatus 40 are apparatuses that perform biometric authentication when authenticating
a user. The authentication apparatus 20, which is a computer that performs user authentication,
is a business-use terminal requiring a high security level, for example. The authentication
apparatus 30 is an ATM (Automated Teller Machine) installed in a financial institution.
The authentication apparatus 40 is an entrance and exit management apparatus for a
security area.
[0029] The authentication server 50 stores identification information for identifying a
user in association with biometric information (template) which is preliminarily registered
prior to biometric authentication. The identification information for identifying
a user is a unique ID (IDentification) provided directly (e.g., user number) or indirectly
(e.g., account number) to the user. The biometric information to be preliminarily
registered includes characteristic information of a characteristic part extracted
from the image information, encoded information of the image information or characteristic
information, or the like.
[0030] In addition, the authentication server 50 is a database server of the authentication
system 10, provided with various databases (e.g., an unaccepted biometric information
database, an unaccepted environment information database, and a guidance information
database described below). The network 51 connects the authentication apparatus 20,
the authentication apparatus 30, the authentication apparatus 40, and the authentication
server 50 communicably in a wired or wireless manner. Various databases may be provided
in the authentication apparatus 20, the authentication apparatus 30, and the authentication
apparatus 40, in place of the authentication server 50.
[0031] The authentication apparatus 20 is configured to include a processing apparatus 21,
a display 22, and a sensor-unit-embedded mouse 24, and also configured to include
a keyboard 23, an IC (Integrated Circuit) card reader/writer 25, etc. as needed. The
sensor-unit-embedded mouse 24 has a sensor unit built therein. The sensor unit, having
an image capturing device, photographs the user's palm, and outputs the captured image
to the processing apparatus 21. The IC card reader/writer 25 reads or writes information
of an IC card 26 of the user. The keyboard 23 and the sensor-unit-embedded mouse 24
accept input operations.
[0032] Here, palm vein authentication in the authentication apparatus 20 is described. A
user requesting authentication inputs identification information for identifying the
user (e.g., user ID) via the keyboard 23, the sensor-unit-embedded mouse 24, or the
IC card reader/writer 25. The authentication apparatus 20 prompts the user to input
biometric information by presentation using the display 22. The user inputs biometric
information by holding the palm above the sensor-unit-embedded mouse 24. Upon receiving
the input of a palm vein image as biometric information, the authentication apparatus
20 performs matching of the input vein image (biometric information) with a registered
template. The registered template may be stored in a storage unit of the processing
apparatus 21, a storage unit of the authentication server 50, or a storage unit of
the IC card 26 of the user.
[0033] The authentication apparatus 30 has a sensor unit 31. The sensor unit 31, having
an image capturing device, photographs the user's palm. The authentication apparatus
30 performs authentication of the user using the captured image. The authentication
apparatus 30, having an IC card reader/writer (not illustrated), performs matching
using a registered template stored in an IC card (e.g., an IC-chip-built-in cash card).
[0034] The authentication apparatus 40 has a numerical keypad 41, an IC card reader/writer
42, and a sensor unit 43. The numerical keypad 41 is used for inputting a password
when password-based authentication is used together. The IC card reader/writer 42
reads or writes information of the user's IC card (not illustrated). The sensor unit
43, having an image capturing device, photographs the user's palm. The authentication
apparatus 40 performs authentication of the user based on the registered template
stored in the IC card and the captured image, and controls opening and closing of
a door 44.
[0035] Next, a configuration which realizes a procedure for the authentication apparatus
20 to perform palm vein authentication will be described referring to FIG. 3. FIG.
3 illustrates a configuration of an authentication apparatus of the second embodiment.
[0036] The authentication apparatus 20 has a control unit 200, a storage unit 201, a notification
unit 202, and a communication unit 203. Furthermore, the authentication apparatus
20 has an image input unit 204, an object extraction unit 205, a palm determination
unit 206, a palm clipping unit 207, a contour correcting unit 208, and a surface information
extraction unit 209. Furthermore, the authentication apparatus 20 has a surface information
analysis unit 210, a surface information correcting unit 211, an unaccepted information
acquisition unit 212, a guidance method selecting unit 213, a biometric information
extraction unit 214, and a matching unit 215.
[0037] The control unit 200 totally controls respective processing units to perform user
authentication. The storage unit 201 stores and retains image information obtained
from the sensor-unit-embedded mouse 24, various databases, and the like. The notification
unit 202 generates and displays on the display 22 desired messages for the user such
as guidance about the manner of holding the palm above the sensor-unit-embedded mouse
24, notification of success or failure of the matching, or the like. In addition,
the notification unit 202 generates and outputs from a loud speaker (not illustrated),
desired audio messages for the user such as guidance about the manner of holding the
palm above the sensor-unit-embedded mouse 24 or notification of success or failure
of the matching, or the like. The communication unit 203 communicates with a sensor
unit embedded in the sensor-unit-embedded mouse 24, an IC chip built in the IC card
reader/writer 25, and a computer connected to the network 51.
[0038] The image input unit 204 inputs the captured image of the living body from the sensor-unit-embedded
mouse 24. The object extraction unit 205 removes the background from the captured
image and extracts the object. The palm determination unit 206 determines whether
or not the object is a palm. When the palm determination unit 206 determines that
the object is not a palm, the image input unit 204 newly inputs a captured image of
the living body from the sensor-unit-embedded mouse 24. In this occasion, the notification
unit 202 may be configured to guide the motion of holding the palm above.
[0039] From the object determined to be a palm by the palm determination unit 206, the palm
clipping unit 207 clips the palm (the fingers and the wrist may be included). The
contour correcting unit 208 corrects the position (backward and forward, rightward
and leftward positional correction), the size (upward and downward height correction),
and orientation (rotational correction) of the clipped palm to the correct position.
[0040] The surface information extraction unit 209 extracts surface information from the
palm image corrected by the contour correcting unit 208. Specifically, the surface
information extraction unit 209 extracts, as surface information, luminance (luminance
information) from the palm image. The surface information extraction unit 209 extracts,
as surface information, not only luminance but also lightness or the like from the
palm image. In addition, the surface information extraction unit 209 may obtain distance
information from the sensor-unit-embedded mouse 24 as information associated with
the palm image, and may obtain the distance between a distance measuring sensor and
the palm surface as surface information.
[0041] The surface information analysis unit 210 analyzes concave/convex sites of the palm
from the surface information extracted by the surface information extraction unit
209. The surface information correcting unit 211 corrects, among the concave/convex
sites analyzed by the surface information analysis unit 210, a concave/convex site
within a correctable range. The surface information analysis unit 210 obtains a palm
image having the concave/convex site corrected, a palm image for which correction
with regard to the concave/convex site is not desired. When the surface information
correcting unit 211 determines that the concave/convex site is not within a correctable
range, the image input unit 204 newly inputs the captured image of the living body
from the sensor-unit-embedded mouse 24. In this occasion, the notification unit 202
may be configured to guide the motion of holding the palm above.
[0042] The biometric information extraction unit 214 extracts biometric information to be
used for matching from the palm image obtained by the surface information analysis
unit 210. Specifically, the biometric information extraction unit 214 extracts a vein
pattern in the palm image, or information for matching included in the vein pattern.
The information for matching includes, for example, characteristics points (edge point
or branch point of a vein) included in the vein pattern, the number of veins crossing
with a straight line binding a characteristics point and a proximate characteristic
point, and a small image centered on a characteristics point. The matching unit 215
compares and performs matching of the biometric information (information for matching)
extracted by the biometric information extraction unit 214 with a registered template
which has been preliminarily registered.
[0043] In this manner, the authentication apparatus 20 rectifies the slight variation of
biometric information and environmental changes by correcting concave/convex sites.
The authentication apparatus 20 reduces the opportunities to perform notification
that guides the living body to a proper posture, by reducing instability of the biometric
information and influence of environmental changes.
[0044] The authentication apparatus 20 has a function of performing a procedure for providing
a more appropriate guidance when the surface information correcting unit 211 determines
that the concave/convex site is not within a correctable range. The unaccepted information
acquisition unit 212 registers the captured image which was unusable for matching
in an unaccepted biometric information database as an unaccepted image. In addition,
the unaccepted information acquisition unit 212 registers the environment information
at the time of capturing the image which was unusable for matching in the unaccepted
environment information database.
[0045] The guidance method selecting unit 213 selects, referring to a guidance information
database, a guidance method corresponding to the captured image which was unusable
for matching. The guidance method selected by the guidance method selecting unit 213
is notified to the user by the notification unit 202.
[0046] In this manner, when the captured image is unusable for matching, the authentication
apparatus 20 is able to present and notify to the user an appropriate guidance method.
In addition, accumulation of causes of failure in the unaccepted biometric information
database and the unaccepted environment information database contributes to enhancement
of the guidance method selected by the guidance method selecting unit 213.
[0047] Next, an exemplary hardware configuration of the authentication apparatus 20 of the
embodiment will be described referring to FIG. 4. FIG. 4 illustrates an exemplary
hardware configuration of the authentication apparatus of the second embodiment.
[0048] The authentication apparatus 20 includes the processing apparatus 21, the display
22, the keyboard 23, the sensor-unit-embedded mouse 24, and the IC card reader/writer
25.
[0049] The entirety of the processing apparatus 21 is controlled by a CPU (Central Processing
Unit) 101. The CPU 101 has a RAM (Random Access Memory) 102, an HDD (Hard Disk Drive)
103, a communication interface 104, a graphic processing unit 105, and an input-output
interface 106 connected thereto via a bus 107.
[0050] The RAM 102 has programs of the OS (Operating System) executed by the CPU 101 and
at least a part of application programs temporarily stored therein. In addition, the
RAM 102 has stored therein various data needed for processing by the CPU 101. The
HDD 103 has the OS and application programs stored therein.
[0051] The graphic processing unit 105 has a display 22 connected thereto. The graphic processing
unit 105 causes an image to be displayed on the screen of the display 22, according
to an instruction from the CPU 101.
[0052] The input-output interface 106 has the keyboard 23, the sensor-unit-embedded mouse
24, and the IC card reader/writer 25 connected thereto. In addition, the input-output
interface 106 allows connection thereto of a portable storage medium interface which
allows writing of information to a portable storage medium 110 and reading of information
from the portable storage medium 110. The input-output interface 106 transmits, to
the CPU 101 via the bus 107, the signal being transmitted from the keyboard 23, the
sensor-unit-embedded mouse 24, the IC card reader/writer 25, and the portable storage
medium interface.
[0053] More specifically, the input-output interface 106 may be connected to the sensor-unit-embedded
mouse 24 via a USB (Universal Serial Bus). Since the processing apparatus 21 receives
the captured image from the sensor unit, USB connection is desirable to be based on
USB 2.0 or later which is connectable in a high speed mode.
[0054] The communication interface 104 is connected to the network 51. The communication
interface 104 transmits and receives data to and from the authentication server 50.
[0055] The processing function of the present embodiment may be realized by a hardware configuration
as described above. The authentication apparatus 30, the authentication apparatus
40, and the authentication server 50 may be realized by a similar hardware configuration.
[0056] The processing apparatus 21 may be configured to include modules respectively including
an FPGA (Field Programmable Gate Array), a DSP (Digital Signal Processer), or the
like, or may be configured not to include the CPU 101. In such a case, the processing
apparatus 21 has a nonvolatile memory (e.g., EEPROM (Electrically Erasable and Programmable
Read Only Memory), a flash memory, a flash memory type memory card) respectively,
and stores the firmware of the modules. Into the nonvolatile memory, the firmware
may be written via the portable storage medium 110 or the communication interface
104. Thus the processing apparatus 21 may also update the firmware by rewriting the
firmware stored in the nonvolatile memory.
[0057] Next, a configuration in which the sensor-unit-embedded mouse 24 obtains image information
and distance information and outputs the information to the processing apparatus 21
will be described referring to FIG. 5. FIG. 5 illustrates the configuration of the
sensor unit of the second embodiment. The sensor unit 31 and the sensor unit 43 may
have a configuration similar to a sensor unit 24a.
[0058] The sensor unit 24a is embedded in the sensor-unit-embedded mouse 24. The sensor
unit 24a includes a control unit 24b, an image capturing unit 24c, a distance measuring
unit 24d, a storage unit 24e, and a communication unit 24f.
[0059] The control unit 24b totally controls respective processing units. The image capturing
unit 24c obtains image information from a target living body. The image capturing
unit 24c includes an image sensor (e.g., CMOS (Complementary Metal Oxide Semiconductor)
sensor, CCD (Charge Coupled Device) sensor, etc.) which photographs the living body,
a condensing lens, and a plurality of near-infrared light-emitting elements (LED:
Light Emitting Diodes) which irradiate the object. The near-infrared light-emitting
elements, provided on the periphery of the image sensor for example, emits near infrared
light toward the object (upward), and the image sensor photographs the object irradiated
by the near infrared light. The image sensor may capture the object palm within a
wide photographing range, through the condensing lens (wide-angle lens) in a wide
area.
[0060] The distance measuring unit 24d obtains information of the distance to the target
living body. The sensor unit 24a is able to measure the photographing timing with
the distance measuring sensor to photograph the palm within a predetermined range
of distance. The image capturing unit 24c may perform continuous photographing (e.g.,
15 frames per second) at a predetermined timing and use one or more of the captured
images for matching.
[0061] The storage unit 24e stores the distance information obtained by the distance measuring
unit 24d and the image information obtained by the image capturing unit 24c in association
with the image information. The communication unit 24f, connected to the communication
unit 203 of the processing apparatus 21, receives instructions from the processing
apparatus 21, and transmits image information and distance information.
[0062] The image captured by the sensor unit 24a is an image obtained by irradiating near
infrared light on the target living body (palm) and photographing the reflected light.
Since hemoglobin in red blood cells flowing through the vein has a reduced amount
of oxygen, such hemoglobin (reduced hemoglobin) has a property of absorbing near infrared
light around 700 to 1000 nanometers. Therefore, holding the palm against the near
infrared light results in less reflection in the part where the vein exists, and thus
the location of the vein becomes recognizable according to the strength/weakness of
the reflected near infrared light. Although extraction of characteristic information
of the captured image becomes easy by the use of a particular light source, the image
is achromatic.
[0063] Next, an authentication procedure performed by the processing apparatus 21 will be
described in detail referring to FIG. 6. FIG. 6 is a flow chart of the authentication
procedure of the second embodiment. The processing apparatus 21 receives an authentication
request from a user and performs the authentication procedure to obtain an authentication
result.
[Step S11] The processing apparatus 21 obtains a registered template. The registered
template may be obtained from a storage unit (HDD 103) of the processing apparatus
21, a storage unit of the authentication server 50, or a storage unit of the IC card
26 of the user. The processing apparatus 21 obtains the registered template corresponding
to the user, based on information (e.g., user ID, card ID) by which the registered
template may be uniquely identified. When the user is not identified at the start
of the authentication procedure, the registered template may be obtained immediately
before the matching.
[Step S12] The processing apparatus 21 obtains, from the sensor-unit-embedded mouse
24, a captured image used for authentication (image input unit 204). [Step S13] The
processing apparatus 21 extracts an object from the captured image (object extraction
unit 205). The processing apparatus 21 determines whether or not the extracted object
is the palm (palm determination unit 206). The processing apparatus 21 clips the palm
from the object which has been determined to be the palm (palm clipping unit 207).
The processing apparatus 21 corrects the image of the clipped palm to the correct
position (contour correcting unit 208).
[Step S14] The processing apparatus 21 determines whether or not the image of the
palm which has been corrected to the correct position is usable for matching. The
determination is performed by comparing the image of the palm which has been corrected
to the correct position with an image of the registered template, or comparing the
image of the palm which has been corrected to the correct position with a model. When
the processing apparatus 21 determines that the image of the palm which has been corrected
to the correct position is usable for matching, the processing apparatus 21 proceeds
to step S19, or proceeds to step S15 when the image is determined to be unusable for
matching.
[Step S15] The processing apparatus 21 extracts surface information from the palm
image which has been corrected to the correct position (surface information extraction
unit 209). The processing apparatus 21 analyzes the concave/convex site of the palm
from extracted surface information, and determines whether or not the surface information
is correctable (surface information analysis unit 210). When the processing apparatus
21 determines that the surface information is correctable, the processing apparatus
21 proceeds to step S18, or proceeds to step S16 when the surface information is not
determined to be correctable.
[Step S16] The processing apparatus 21 performs an unaccepted information acquisition
procedure (unaccepted information acquisition unit 212). The unaccepted information
acquisition procedure is a procedure of registering an unaccepted image in an unaccepted
biometric information database and registering environment information at the time
of capturing the unaccepted image in an unaccepted environment information database.
[Step S17] The processing apparatus 21 notifies the user of reacquisition in order
to newly obtain an image for authentication. In addition, the processing apparatus
21 performs guidance for placing the user's palm to the correct position in order
to newly obtain an appropriate image for authentication (guidance method selecting
unit 213, notification unit 202).
[Step S18] When the surface information is within a correctable range, the processing
apparatus 21 corrects the surface information (surface information correcting unit
211).
[Step S19] The processing apparatus 21 extracts biometric information to be used for
matching, from a palm image having corrected surface information or a palm image not
requiring correction of the surface information (biometric information extraction
unit 214).
[Step S20] The processing apparatus 21 compares the extracted biometric information
with the registered template which has been preliminarily registered to perform matching
(matching unit 215).
[Step S21] The processing apparatus 21, when the matching is successful, in other
words, when determining that the degree of matching exceeds a predetermined threshold,
proceeds to step S22 based on the successful matching, or when the matching is unsuccessful,
proceeds to step S23 based on the unsuccessful matching.
[Step S22] Upon receiving the result of successful matching, the processing apparatus
21 determines identity confirmation and, subsequent to performing a desired procedure
associated with the successful authentication, terminates the authentication procedure.
[Step S23] Upon receiving the result of unsuccessful matching, the processing apparatus
21 determines identity rejection and, subsequent to performing a desired procedure
associated with the failed authentication, terminates the authentication procedure.
[0064] Next, a surface information extraction procedure performed by the surface information
extraction unit 209 will be described in detail referring to FIGS. 7 to 10. FIG. 7
is a flow chart of the surface information extraction procedure of the second embodiment.
FIG. 8 illustrates an evaluation unit of the surface information of the second embodiment.
FIG. 9 illustrates normalization of luminance distribution of the second embodiment.
FIG. 10 illustrates examples of surface information extraction of the second embodiment.
The surface information extraction procedure is performed prior to determining whether
or not correction of surface information is possible at step S15 of the authentication
procedure.
[Step S31] The surface information extraction unit 209 obtains, from the palm image,
luminance information of the entire palm. The region for which the surface information
extraction unit 209 obtains luminance information is the entire palm region 61 corresponding
to the palm of the hand 60 (see FIG. 8). Although the entire palm region 61 is a circular
region, for example, it may be, without being limited thereto, an oval, a rectangle,
polygons of other types, or a region surrounded by a free closed curve.
[Step S32] The surface information extraction unit 209 divides the entire palm region
61 into a plurality of subregions 62. The location of providing each subregion 62
has been preliminarily set. Each subregion 62 is arranged allowing existence of mutually
overlapping regions (see FIG. 8).
[Step S33] The surface information extraction unit 209 obtains luminance information
on one subregion 62.
[Step S34] The surface information extraction unit 209 normalizes the obtained luminance
information. The surface information extraction unit 209 performs normalization of
the luminance information using shift of luminance distribution and correction of
luminance distribution range. For example, the surface information extraction unit
209 generates, from the obtained luminance information, a luminance distribution 64
within the range of gray scale (0 to 255). The luminance distribution 64 has a distribution
range lower limit Th01, a distribution range upper limit Th02, and a distribution
range W0. The surface information extraction unit 209 corrects and normalizes the
luminance distribution 64 to a distribution range lower limit Th11, a distribution
range upper limit Th12, and a distribution range W1 of a model luminance distribution
65 (see FIG. 9).
[0065] The above normalization makes it possible to objectively evaluate the state of surface
information of the palm even when there exists variation of the object such as color
or complexion of the user's palm, or variation of the photographing environment such
as being outdoor or indoor.
[Step S35] The surface information extraction unit 209 divides the subregion 62 into
a plurality of finer subregions 63. The location of providing each finer subregion
63 has been preliminarily set. Each finer subregion 63 is arranged allowing existence
of mutually overlapping regions (see FIG. 8).
[Step S36] The surface information extraction unit 209 obtains corrected luminance
information for one finer subregion 63.
[Step S37] The surface information extraction unit 209 evaluates, for one finer subregion
63 for which luminance information has been obtained, the degree of luminance and
the size of luminance distribution. For example, the surface information extraction
unit 209 evaluates the degree (brightness) of luminance and the size of luminance
distribution by comparison with an ideal value. More specifically, the surface information
extraction unit 209 evaluates the size of luminance distribution based on the range
of luminance distribution within a predetermined range including the mode, and evaluates
the degree of luminance by the average luminance of the distribution range to be evaluated.
Evaluation of the degree of luminance is such as, in comparison with an ideal value,
"considerably dark", "dark", "standard", "bright", and "considerably bright". In addition,
evaluation of the size of luminance distribution is such as "wide", "narrow", and
"moderate", in comparison with an ideal value.
[Step S38] The surface information extraction unit 209 determines, for the subregion
62 being evaluated, whether or not evaluation of the degree of luminance and the size
of luminance distribution has been completed for all the finer subregions 63. The
surface information extraction unit 209, when not having completed evaluation for
all the finer subregions 63, proceeds to step S36, or proceeds to step S39 when having
completed evaluation.
[Step S39] The surface information extraction unit 209 evaluates the corresponding
subregion 62 from evaluation of all the finer subregions 63. The surface information
extraction unit 209 calculates the size of luminance distribution of subregion 62
and the degree of luminance by evaluation of the subregion 62.
[Step S40] The surface information extraction unit 209 determines, for the entire
palm region 61, whether or not evaluation has been completed for all the subregions
62. The surface information extraction unit 209, when not having completed evaluation
for all the subregions 62, proceeds to step S33, or terminates the surface information
extraction procedure when having completed evaluation.
[0066] FIG. 10 illustrates examples in which the surface information extraction unit 209
has extracted surface information from the entire palm region 61a in the manner described
above. When the luminance distribution exists within a predetermined range in comparison
with a model (ideal value), the surface information extraction unit 209 extracts a
uniform luminance distribution as surface information for the entire palm region 61a,
as illustrated in part (1) of FIG. 10. When the luminance distribution is non-uniform
in comparison with the model, the surface information extraction unit 209 extracts
a non-uniform luminance distribution as surface information for the entire palm region
61b, as illustrated in part (2) of FIG. 10. The entire palm region 61b has, as non-uniform
luminance distributions, a luminance distribution 67a and a luminance distribution
67b. The luminance distribution 67a is evaluated as being "dark", and the luminance
distribution 67b is evaluated as being "bright". Since the dark part indicates a concave
and the bright part indicates a convex, it is recognized that the entire palm region
61b is of a slightly rounded palm. When the luminance distribution is non-uniform
in comparison with the model, the surface information extraction unit 209 extracts
a non-uniform luminance distribution as surface information for the entire palm region
61c, as illustrated in part (3) of FIG. 10. The entire palm region 61c has a luminance
distribution 67c and a luminance distribution 67d as non-uniform luminance distributions.
The luminance distribution 67c is evaluated as being "considerably dark", and the
luminance distribution 67d is evaluated as being "considerably bright". Since the
considerably dark part indicates a strong concavity and the considerably bright part
indicates a strong convexity, it is recognized that the entire palm region 61c is
of a slightly rounded palm.
[0067] In the manner described above, the authentication apparatus 20 is able to recognize
the state of the palm based on the surface information extracted by the surface information
extraction unit 209.
[0068] Here, a variation of the evaluation unit of the surface information described referring
to FIG. 8 will be described referring to FIG. 11. FIG. 11 illustrates a variation
of the evaluation unit of the surface information of the second embodiment.
[0069] The entire palm region 68 is a region, of the hand 60, for which the surface information
extraction unit 209 obtains luminance information. The entire palm region 68 is a
region having a plurality of subregions 69 collected therein. The location of arranging
each subregion 69 has been preliminarily set. Each subregion 69 has no mutually overlapping
regions and is arranged adjacent to each other. A subregion 69 is a region having
a plurality of finer subregions 70 collected therein. The location of arranging each
finer subregion 70 has been preliminarily set. Each finer subregion 70 has no mutually
overlapping regions and is arranged adjacent to each other. A variation of the evaluation
unit of the surface information is different from the second embodiment in that in
the variation, the entire palm region 68, the subregion 69, and the finer subregion
70 are respectively different in shape, whereas in the second embodiment, the entire
palm region 61, the subregion 62, and the finer subregion 63 are respectively homothetic.
[0070] Next, a surface information analysis procedure performed by the surface information
analysis unit 210 will be described in detail, referring to FIGS. 12 and FIG. 13.
FIG. 12 is a flow chart of the surface information analysis procedure of the second
embodiment. FIG. 13 illustrates examples of surface information analysis of the second
embodiment. The surface information analysis procedure is performed subsequent to
surface information extraction at step S15 of the authentication procedure.
[Step S41] The surface information analysis unit 210 obtains, for each site, surface
information (strength/weakness and range of concavity/convexity) extracted by the
surface information extraction unit 209. Here, a site, which refers to a region of
the palm divided into a plurality of regions, is predefined. Each site is related
in association with one or more of the subregions 62 described above. For example,
there are five types of parts, i.e., a central part 91 located at the center of the
palm of the hand 60, an upper part 95 and a lower part 93 located above and below
the central part 91, and a thumb part 94 and a little finger part 92 located at the
right and left of the central part 91 (part (1) of FIG. 13). Alternatively, each site
may be defined in association with the skeleton and muscles of a human, such as being
divided into six parts, i.e., the first to fifth metacarpal bones and the carpal bone.
[Step S42] The surface information analysis unit 210 determines, for one of the plurality
of sites, whether or not it is a strong convex range or a strong concave range. Determination
of whether a site is a strong convex range or a strong concave range is performed
by comparison with a predetermined threshold. When the surface information analysis
unit 210 determines that either a strong convex range or a strong concave range exists
in a site to be determined, the surface information analysis unit 210 proceeds to
step S43. When the surface information analysis unit 210 determines that neither a
strong convex range nor a strong concave range exists in the site to be determined,
the surface information analysis unit 210 proceeds to step S44.
[Step S43] Assuming that the site to be determined is uncorrectable, the surface information
analysis unit 210 sets a retry flag and terminates the surface information analysis
procedure. Setting of the retry flag causes the authentication apparatus 20 to perform
re-acquisition of an image for authentication.
[Step S44] The surface information analysis unit 210 determines whether or not the
site to be determined is a weak convex range. Determination of a weak convex range
is performed by comparison with a predetermined threshold. When the surface information
analysis unit 210 determines that there is a weak convex range in the site to be determined,
the surface information analysis unit 210 proceeds to step S45. The surface information
analysis unit 210, when determining that there is no weak convex range in the site
to be determined, proceeds to step S46.
[Step S45] The surface information analysis unit 210 sets a convex correction flag
to the site to be determined.
[Step S46] the surface information analysis unit 210 determines whether or not the
site to be determined is a weak concave range. Determination of being a weak concave
range is performed by comparison with a predetermined threshold. The surface information
analysis unit 210, when determining that there is a weak concave range in the site
to be determined, proceeds to step S47. The surface information analysis unit 210,
when determining that there is no weak concave range in the site to be determined,
proceeds to step S48.
[Step S47] The surface information analysis unit 210 sets a concave correction flag
to the site to be determined.
[Step S48] The surface information analysis unit 210 determines whether or not analysis
has been completed for all of the plurality of sites. When analysis has not been completed
for all of the plurality of sites, the surface information analysis unit 210 proceeds
to step S42 in order to analyze the site for which analysis has not been completed
yet. When analysis has been completed for all of the plurality of sites, the surface
information analysis unit 210 terminates the surface information analysis procedure.
[0071] As thus described, the surface information analysis unit 210 completes the analysis
of surface information (concavity/convexity information of the palm surface) by determining
the validity of the set of the convex correction flag and the concave correction flag
for all of the plurality of sites. In addition, the surface information analysis unit
210 sets a retry flag when there is a strong convex range or a strong concave range
in at least one of the plurality of sites, and regards the image to be analyzed as
inappropriate for authentication.
[0072] An exemplary surface information analysis evaluated to be inappropriate for such
an authentication is illustrated in parts (2) to (4) of FIG. 13. A hand 60a provides
an exemplary surface information analysis for a strong convex part 71a and a strong
concave part 72a. The hand 60a may be evaluated to be in a state with the palm being
rounded. A hand 60b provides an exemplary surface information analysis for a strong
convex 71b and a strong concave 72b. The hand 60b may be evaluated to be in a state
that the thumb is lower than the palm. A hand 60c provides an exemplary surface information
analysis for a strong convex 71c and a strong concave 72c. The hand 60c may be evaluated
to be in a state with the little finger being lower than the palm. As thus described,
since the result of analysis by the surface information analysis unit 210 may evaluate
the state of the hand 60, it becomes possible to set a retry flag to indicate an inappropriate
posture and provide an appropriate guidance when re-obtaining an image for authentication.
[0073] Next, a surface information correcting procedure performed by the surface information
correcting unit 211 will be described in detail, referring to FIG. 14. FIG. 14 is
a flow chart of the surface information correcting procedure of the second embodiment.
The surface information correcting procedure is performed at step S18 of the authentication
procedure.
[Step S51] The surface information correcting unit 211 determines whether or not a
convex correction flag is set for the each site analyzed by the surface information
analysis unit 210. The surface information correcting unit 211, when determining that
a convex correction flag has been set, proceeds to step S52, or proceeds to step S53
when determining that the convex correction flag has not been set.
[Step S52] The surface information correcting unit 211 performs a surface reflection
removal procedure to remove surface reflection of the palm image. Details of the surface
reflection removal procedure will be described later, referring to FIGS. 15 to 17.
[Step S53] The surface information correcting unit 211 determines whether or not there
exists comparative data to be compared with the palm image. When there exists comparative
data, the surface information correcting unit 211 proceeds to step S56, or proceeds
to step S54 when there is no comparative data. The comparative data is a registered
template of a user, for example. The registered template may be obtained based on
a user ID input by a user. When a registered template of the user is not obtainable,
such as when preliminary input of the user ID is not needed, the surface information
correcting unit 211 may use comparative data as a standard model. The comparative
data when using a registered template may be a marginal model for which a predetermined
tolerance is provided based on the registered template, instead of the registered
template itself.
[Step S54] The surface information correcting unit 211 determines whether or not a
concave correction flag is set for each site analyzed by the surface information analysis
unit 210. The surface information correcting unit 211, when determining that a concave
correction flag has been set, proceeds to step S55, or terminates the surface information
correcting procedure when determining that a concave correction flag has not been
set.
[Step S55] The surface information correcting unit 211 performs luminance correction
for each site in the absence of comparative data of a palm image. The surface information
correcting unit 211 performs luminance correction by offsetting the average value
of luminance for each site so as to conform with the overall average, for example.
For luminance correction, the median or the mode may also be used without being limited
to the average luminance for each site. In addition, luminance correction for each
site may perform luminance correction with different rules for each site. After having
performed luminance correction for each site, the surface information correcting unit
211 terminates the surface information correcting procedure.
[Step S56] When there exists comparative data of the palm image, the surface information
correcting unit 211 overviews the entire palm to evaluate the concavity/convexity
matching. When the evaluation of concavity/convexity matching falls within a range
of a predetermined threshold, the surface information correcting unit 211 terminates
the surface information correcting procedure. When, on the other hand, the evaluation
of concavity/convexity matching does not fall within a range of the predetermined
threshold, the surface information correcting unit 211 proceeds to step S57.
[Step S57] The surface information correcting unit 211 performs luminance correction,
for a range with a low evaluation of concavity/convexity matching, so as to correct
the average value of luminance which has expanded to peripheral areas. The surface
information correcting unit 211 performs luminance correction by offsetting the average
value of luminance of a site to be corrected and the peripheral region thereof so
as to conform with the overall average, for example.
[Step S58] The surface information correcting unit 211 overviews the entire palm to
reevaluate the concavity/convexity matching. When the re-evaluation of concavity/convexity
matching falls within a range of a predetermined threshold, the surface information
correcting unit 211 terminates the surface information correcting procedure. When,
on the other hand, the re-evaluation of concavity/convexity matching does not fall
within a range of a predetermined threshold, the surface information correcting unit
211 proceeds to step S59.
[Step S59] Assuming that the palm image is uncorrectable, the surface information
correcting unit 211 sets a retry flag and terminates the surface information correcting
procedure. Setting of the retry flag causes the authentication apparatus 20 to perform
re-acquisition of an image for authentication.
[0074] In this manner, the surface information correcting unit 211 rectifies the slight
variation of biometric information and environmental changes within tolerance by correcting
concave/convex sites. Accordingly, the authentication apparatus 20 reduces the opportunities
to perform re-acquisition of an image for authentication.
[0075] Next, a surface reflection removal procedure performed by the surface information
correcting unit 211 will be described in detail, referring to FIGS. 15 to 17. FIG.
15 is a flow chart of the surface reflection removal procedure of the second embodiment.
FIG. 16 illustrates removal of surface reflection from the luminance distribution
of the second embodiment. FIG. 17 illustrates examples of surface reflection removal
process of the second embodiment. The surface reflection removal procedure is performed
at step S52 of the surface information correcting procedure.
[Step S61] The surface information correcting unit 211 estimates the luminance model
of the palm from the palm image (part (1) of FIG. 17). The surface information correcting
unit 211 obtains, by a spline function, an estimated luminance model 74 from a luminance
graph 73 illustrating the result of scanning the palm surface luminance in the lateral
direction. The surface information correcting unit 211 removes a high-frequency component
such as the vein which is darker than the bright convex and the periphery, using a
low-order (e.g., second order) spline function. The surface information correcting
unit 211 estimates the luminance model of the entire palm from a plurality of estimated
luminance models 74 displaced in the vertical direction in a similar manner. In addition,
known methods may be used for the luminance model of the palm image such as estimating
from the luminance gradient, for example.
[Step S62] The surface information correcting unit 211 extracts, from the difference
between the luminance graph 73 and the estimated luminance model 74, a convex part
(e.g., convex part 71d, convex part 71e) exhibiting surface reflection (e.g., convex
part extracted image 75 (part (2) of FIG. 17)). The surface information correcting
unit 211 obtains a surface reflection emphasized image (e.g., emphasized image 76
(part (3) of FIG. 17)) emphasizing surface reflection from the palm image.
[Step S63] The surface information correcting unit 211 estimates the surface reflection
components included in the surface reflection emphasized image.
[Step S64] The surface information correcting unit 211 generates a surface reflection
smoothed image (e.g., smoothed image 77 (part (4) of FIG. 17)) having the surface
reflection components removed from the surface reflection emphasized image to smooth
surface reflection.
[Step S65] The surface information correcting unit 211 corrects luminance of the palm
image based on the generated surface reflection smoothed image, and terminates the
surface reflection removal procedure. Known methods may be used for correction of
the luminance of the palm image, such as removing the effects of non-uniform illumination,
for example.
[0076] As thus described, the surface information correcting unit 211 may preferably remove
surface reflection by emphasizing surface reflection of the palm image and subsequently
removing surface reflection components.
[0077] Next, an unaccepted information acquisition procedure performed by the unaccepted
information acquisition unit 212 will be described in detail, referring to FIGS. 18
to 22. FIG. 18 is a flow chart of the unaccepted information acquisition procedure
of the second embodiment. FIG. 19 illustrates an example of unaccepted biometric information
of the second embodiment. FIG. 20 illustrates examples of unaccepted image of the
second embodiment. FIG. 21 illustrates an example of unaccepted environment information
of the second embodiment. FIG. 22 illustrates exemples of photographing environment
image of the second embodiment. The unaccepted information acquisition procedure is
performed at step S16 of the authentication procedure when it is not possible to correct
surface information.
[Step S71] The unaccepted information acquisition unit 212 outputs, as unaccepted
biometric information, a captured image which is impossible to correct surface information
and information on the captured image, and updates an unaccepted biometric information
database 52.
[Step S72] The unaccepted information acquisition unit 212 determines whether or not
there exists a palm in the photographing range. The unaccepted information acquisition
unit 212 determines whether or not there exists a palm in the photographing range
by obtaining a current captured image from the sensor-unit-embedded mouse 24. The
unaccepted information acquisition unit 212, when determining that there exists a
palm in the photographing range, proceeds to step S73, or proceeds to step S74 when
determining that there is no palm in the photographing range.
[Step S73] The unaccepted information acquisition unit 212 instructs the notification
unit 202 to perform notification of withdrawing the palm from the photographing range.
Upon receiving the instruction, the notification unit 202 prompts, by display or voice,
the user to withdraw the palm from the photographing range. In this manner, the unaccepted
information acquisition unit 212 waits for the palm to be withdrawn from the photographing
range.
[Step S74] The unaccepted information acquisition unit 212 obtains a video image (environmental
video image) with no palm in the photographing range. The unaccepted information acquisition
unit 212 obtains a current captured image from the sensor-unit-embedded mouse 24,
and obtains a video image with no palm in the photographing range.
[Step S75] The unaccepted information acquisition unit 212 outputs, as unaccepted
environment information, information on the obtained environmental video image and
the environment (unaccepted environment) that led to acquisiton of the captured image
for which surface information is uncorrectable, and updates the unaccepted environment
information database 53. After having updated the unaccepted environment information
database 53, the unaccepted information acquisition unit 212 terminates the unaccepted
information acquisition procedure.
[0078] Unaccepted biometric information 300 is an example of unaccepted biometric information
updated at step S71. The unaccepted biometric information 300 is an example of unaccepted
biometric information managed by the unaccepted biometric information database 52.
The unaccepted biometric information includes the information on the palm image which
turned out to be unaccepted by matching, such as identification number, date, time,
user ID, retry (number of retry times), unaccepted living body image, and failure
reason, and information on the palm image.
[0079] Identification number refers to the identification information for uniquely specifying
a matching which turned out to have failed. Date and time respectively refer to the
date and time of the matching which turned out to have failed. Time may be information
in units of seconds, as well as hours and minutes. User ID refers to the identification
information for uniquely specifying a user. Retry refers to the accumulated number
of times the retry flag is set. Unaccepted living body image refers to the palm image
used for matching. For example, a palm image 95 is an unaccepted living body image
having a strong convex part 71f (part (1) of FIG. 20). In addition, a palm image 96
is an unaccepted living body image having a strong convex part 71g and a strong concave
part 72g (part (2) of FIG. 20). Failure reason refers to the reason why the palm image
turned out to be unaccepted by matching.
[0080] Unaccepted environment information 310 is an example of unaccepted environment information
updated at step S75. The unaccepted environment information 310 is an example of unaccepted
environment information managed by unaccepted environment information database 53.
The unaccepted environment information is the information on the environment which
turned out to be unaccepted by matching, such as identification number, date, time,
user ID, unaccepted environment image, sensor ID, illumination, temperature, humidity,
physical condition, or the like.
[0081] Identification number refers to the identification information for uniquely specifying
a matching which turned out to have failed. Date and time respectively refer to the
date and time of the matching which turned out to have failed. Time may be information
in units of seconds, as well as hours and minutes. User ID refers to the identification
information for uniquely specifying a user. Unaccepted environment image refers to
the photographing environment image at the time of image-capturing of the palm (matching).
For example, a photographing environment image 78 is a good photographing environment
image (part (1) of FIG. 22). On the other hand, a photographing environment image
79 is an unaccepted environment image with a fluorescent lamp 80 appearing therein
(part (2) of FIG. 22). In addition, a photographing environment image 81 is an unaccepted
environment image with strong outside light 82 appearing (part (3) of FIG. 22). In
addition, a photographing environment image 83 is an unaccepted environment image
with an unknown light 84 appearing (part (4) of FIG. 22). These unaccepted environment
images do not always include the reason of matching failure in the photographing environment.
Sensor ID refers to the identification information for uniquely specifying the ID
of the sensor unit which has captured the palm image. Illumination refers to the information
indicating ON/OFF of illumination of the ambient environment of the authentication
apparatus 20 at the time of photographing of the palm. Temperature and humidity respectively
refer to the temperature and humidity in the ambient environment of the authentication
apparatus 20. Physical condition refers to the physical condition of the user.
[0082] In order to collect information on the ambient environment, the authentication apparatus
20 may be provided with a sensor (not illustrated) which measures the temperature,
humidity, illuminance, or the like. In addition, the authentication apparatus 20 is
able to obtain, by communication, ambient environment information from a management
apparatus (not illustrated) which manages illumination and air conditioning. In addition,
the authentication apparatus 20 is able to obtain physical condition of the user from
an input apparatus which is not illustrated. The authentication apparatus 20 may also
obtain other ambient environment information such as weather, self-evaluation of the
motion of holding the palm, or the like.
[0083] The authentication apparatus 20 allows a more appropriate guidance of the palm by
enriching the information accumulated in the unaccepted biometric information database
52 and the unaccepted environment information database 53. In addition, enrichment
of the information accumulated in the unaccepted biometric information database 52
and the unaccepted environment information database 53 contributes to improvement
of extraction, analysis, and correction of surface information by the authentication
apparatus 20.
[0084] Next, a guidance method selection procedure performed by the guidance method selecting
unit 213 will be described in detail, referring to FIGS. 23 to 25. FIG. 23 is a flow
chart of the guidance method selection procedure of the second embodiment. FIG. 24
illustrates an exemplary guidance information database of the second embodiment. FIG.
25 illustrates an exemplary guidance presentation screen of the second embodiment.
The guidance method selection procedure is performed at step S17 of the authentication
procedure.
[Step S81] The guidance method selecting unit 213 determines whether or not there
exists a registered template corresponding to a user. When there exists a registered
template corresponding to a user, the guidance method selecting unit 213 proceeds
to step S82, or proceeds to step S83 when there is no registered template.
[Step S82] The guidance method selecting unit 213 selects a registered template as
a reference for comparison with the palm image.
[Step S83] The guidance method selecting unit 213 selects a standard model as a reference
for comparison with the palm image.
[Step S84] The guidance method selecting unit 213 identifies, from the concavity/convexity
information (surface information), inclination/deformation of the palm. The concavity/convexity
information to be used for identification may be the concavity/convexity information
analyzed by the surface information analysis unit 210, or the concavity/convexity
information may be newly analyzed along with identifying the reference for comparison.
[Step S85] The guidance method selecting unit 213 obtains, from a guidance information
database 54, guidance information corresponding to the identified inclination/deformation
of the palm.
[Step S86] When the guidance method selecting unit 213 successfully obtains, from
the guidance information database 54, guidance information corresponding to the identified
inclination/deformation of the palm, the guidance method selecting unit 213 proceeds
to step S87. When, on the other hand, the guidance method selecting unit 213 failed
to obtain, from the guidance information database 54, guidance information corresponding
to the identified inclination/deformation of the palm, the guidance method selecting
unit 213 proceeds to step S88.
[Step S87] The guidance method selecting unit 213 performs guidance notification according
to the guidance information obtained from the guidance information database 54, and
terminates the guidance method selection procedure.
[Step S88] The guidance method selecting unit 213 performs notification of guiding
the palm to a correct position at which the palm is to be held, and terminates the
guidance method selection procedure.
[0085] Guidance information 320 is an example of guidance information obtained at step S85.
The guidance information 320 is an example of guidance information managed by the
guidance information database 54. The guidance information includes information for
determining the guidance method, such as identification number, concave state and
convex state of each site (site 1, site 2, ...), overall state overviewing the plurality
of sites as a whole. In addition, the guidance information 320 is information on guidance
notification such as state messages corresponding to the overall state, guidance messages,
retry messages, or the like.
[0086] Identification number refers to the identification information for uniquely specifying
guidance information. A combination of the concavity/convex state of each site identifies
the overall state. The overall state corresponds to the concavity/convex state for
each of one or more sites. State message refers to the message indicating the state
of the user's palm. Guidance message refers to the message for guiding the palm to
a correct position. Retry message refers to the message indicating the degree of guidance
in comparison with the previously captured posture.
[0087] Accordingly, the authentication apparatus 20 performs notification such as that on
the guidance presentation screen 85. The guidance presentation screen 85 displays
image-based guidance presentations 86 and 87, and a message presentation 88 which
is a message-based guidance presentation. The guidance presentation 86, which is an
image looking at the palm from above, displays the posture of the correct position
(standard model) and the posture at the image capturing position in a comparable manner.
It suffices that the guidance presentation 86 is useful for grasping the displacement
in the horizontal direction, and an image looking at the palm from below may also
be used. The guidance presentation 87, which is an image looking at the palm from
the side, displays the posture of the correct position and the posture at the image
capturing position (estimated from analysis of surface information) in a comparable
manner. It suffices that the guidance presentation 87 is useful for grasping the displacement
in the vertical direction. Although a captured image may be used for the guidance
presentation 86, it may also be CG (Computer Graphic). The guidance presentation 87
may use CG. The guidance presentations 86 and 87 display the contour of the posture
at the correct position with a solid line and the contour of the posture at the image
capturing position with a dashed line, for ease of comparison.
[0088] The message presentation 88 includes a state message 89, a guidance message A90,
and a guidance message B91. The state message 89 indicates the posture that caused
matching failure, in order to correct the posture of which the user is unaware. For
example, the state message 89 indicates that "your finger is slightly bent". The guidance
message A90 is a message which alarms the user of the attitude when being photographed,
in order to correct the instability of the posture of which the user is unaware. For
example, the message A90 provides an instruction such as "please relax". The guidance
message B91 is a message which specifically indicates an incorrect posture of the
user. For example, the guidance message B91 provides a guidance such as "hold your
palm so that the entire palm looks flat when seen from the side". The authentication
apparatus 20 may provide audio notification in addition to, or in place of the message
presentation 88.
[0089] As thus described, since the authentication apparatus 20 provides the user with evaluation
of the manner of holding the palm (notification of the state message 89), improvement
of the user's learning speed of how to hold the palm may be expected to be enhanced.
In addition, since the authentication apparatus 20 alarms the user of the attitude
when being photographed (notification of the guidance message A 90), instability of
the posture of which the user is unaware is expected to be corrected. In addition,
since the authentication apparatus 20 specifically indicates an incorrect posture
of the user (notification of the guidance presentation 86, the guidance presentation
87, and the guidance message B 91), the user is expected to appropriately correct
the posture.
[0090] In addition, the authentication apparatus 20 need not access the registered template
when performing guidance notifications in comparison with the standard model. Accordingly,
the authentication apparatus 20 is also able to apply guidance notification when performing
preliminary matching with the standard model prior to matching using the registered
template.
[0091] Next, a more specific description will be provided using a third embodiment.
[Third embodiment]
[0092] FIG. 26 is a flow chart of a guidance method selection procedure of the third embodiment.
The guidance method selection procedure of the third embodiment is different from
that of the second embodiment in that guidance notification is performed according
to the number of retry times.
[Step S91] The guidance method selecting unit 213 identifies inclination/deformation
of the palm from the concavity/convexity information (surface information) analyzed
by the surface information analysis unit 210.
[Step S92] The guidance method selecting unit 213 obtains, from the guidance information
database 54, guidance information corresponding to the identified inclination/deformation
of the palm.
[Step S93] The guidance method selecting unit 213 obtains the accumulated number of
times the retry flag is set (number of retry times).
[Step S94] The guidance method selecting unit 213 determines whether or not the number
of retry times is equal to or smaller than a predetermined default value. When the
number of retry times is equal to or smaller than the default value, the guidance
method selecting unit 213 proceeds to step S96, or proceeds to step S95 when the default
value is exceeded.
[Step S95] The guidance method selecting unit 213 identifies, from a plurality of
causes of failure, a particular cause of failure occurring with a significant frequency,
and performs notification for alarming as to the cause of failure occurring with a
significant frequency.
[Step S96] When the guidance method selecting unit 213 successfully obtains guidance
information corresponding to the identified inclination/deformation of the palm from
the guidance information database 54, the guidance method selecting unit 213 proceeds
to step S97. When, on the other hand, the guidance method selecting unit 213 failed
to obtain guidance information corresponding to the identified inclination/deformation
of the palm from the guidance information database 54, the guidance method selecting
unit 213 proceeds to step S98.
[Step S97] The guidance method selecting unit 213 performs guidance notification according
to the guidance information obtained from the guidance information database 54, and
terminates the guidance method selection procedure.
[Step S98] The guidance method selecting unit 213 performs notification of guiding
the correct position at which the palm is to be held, and terminates the guidance
method selection procedure.
[0093] Accordingly, the authentication apparatus 20 is able to appropriately indicate the
trend of failures made by the user, as well as the cause of the last failure.
[Fourth embodiment]
[0094] Next, a fourth embodiment will be described, referring to FIGS. 27 to 31. The authentication
apparatus of the fourth embodiment is different from that of the second embodiment
in that the surface information of the captured image may be corrected without preliminarily
performing extraction and analysis of the surface information.
[0095] First, a configuration of an authentication apparatus 20a for performing a procedure
of palm vein authentication will be described, referring to FIG. 27. FIG. 27 illustrates
a configuration of an authentication apparatus of the fourth embodiment. Components
similar to those of the authentication apparatus 20 of the second embodiment are provided
with identical reference numerals with description thereof being omitted.
[0096] The authentication apparatus 20a has the control unit 200, the storage unit 201,
the notification unit 202, the communication unit 203, the image input unit 204, the
object extraction unit 205, the palm determination unit 206, the palm clipping unit
207, and the contour correcting unit 208. Furthermore, the authentication apparatus
20a includes a surface information correcting unit 211a, the unaccepted information
acquisition unit 212, the guidance method selecting unit 213, the biometric information
extraction unit 214, and the matching unit 215.
[0097] The surface information correcting unit 211a performs correction to remove surface-reflected
light and high-frequency components from the palm image corrected by the contour correcting
unit 208. When correction by the contour correcting unit 208 is not needed, the surface
information correcting unit 211a may perform correction to remove surface-reflected
light and high-frequency components from the captured image of the palm.
[0098] Next, a surface information correcting procedure performed by the surface information
correcting unit 211a will be described, referring to FIGS. 28 to 31. FIG. 28 is a
flow chart of the surface information correcting procedure of the fourth embodiment.
FIG. 29 is a flow chart of a palm luminance model generating procedure of the fourth
embodiment. FIG. 30 illustrates exemples of the surface information correcting procedure
of the fourth embodiment. FIG. 31 illustrates luminance graphs of the fourth embodiment,
as well as a state of the luminance corrected image with surface reflection and high
frequencies having been removed from the luminance graph.
[Step S101] The surface information correcting unit 211a obtains a captured image
of a palm (e.g., palm image 350). The palm image 350 is an image of a palm captured
by near infrared irradiation. The palm image 350 is a gray scale image having 256
gradations from 0 to 255, for example. Parts (1) to (6) of FIG. 30 schematically illustrate
the gray scale image having 256 gradations (luminance distribution) using lines dividing
between predetermined gradations. The luminance distribution illustrated in parts
(1) to (6) of FIG. 30 is dark in the background and bright in the part of the palm.
[Step S102] The surface information correcting unit 211a performs a palm luminance
model generating procedure which generates a luminance model of a palm (e.g., luminance
model 351) from a captured image of a palm (e.g., palm image 350). Details of the
palm luminance model generating procedure will be described later.
[Step S103] The surface information correcting unit 211a extracts surface-reflected
light (e.g., surface-reflected light 352) from the captured image of the palm (e.g.,
palm image 350) and the luminance model (e.g., luminance model 351). The surface-reflected
light may be extracted from the difference between the captured image of the palm
and the luminance model. Specifically, surface-reflected light may be extracted by
obtaining the maximum value of the luminance of the captured image of the palm and
the luminance of the luminance model for each pixel, and subtracting the luminance
of the luminance model from the maximum value. The surface-reflected light includes
specular-reflected light, i.e., light from the light source (including outside light
and the like, without being limited to light sources irradiating the palm at the time
of image-capturing of the palm) specularly reflected on the palm.
[Step S104] The surface information correcting unit 211a identifies high-frequency
components (e.g., high-frequency component 353) included in surface-reflected light
(e.g., surface-reflected light 352). The high-frequency components mentioned here
refers to frequency components that are higher than the frequency component associated
with the biometric information (vein of a palm) used for biometric authentication.
High-frequency components are noise components appearing from sensitivity characteristics
inherent, for example, to the imaging device that performed image-capturing (imaging)
of the palm, the peripheral environment, or the like.
[0099] The surface information correcting unit 211a may specify high-frequency components
by a Top-hat by Reconstruction procedure based on an Opening procedure using a Structuring
Element, which is a kind of Gray-Scale Morphology procedure. Particularly, the surface
information correcting unit 211a may identify high-frequency components from the result
of processing by selecting a structure element having a high correlation with the
high-frequency components.
[Step S105] The surface information correcting unit 211a removes surface-reflected
light (e.g., surface-reflected light 352) and high-frequency components (e.g., high-frequency
component 353) from the captured image of the palm (e.g., palm image 350). The surface
information correcting unit 211a further generates a smoothed image (e.g., smoothed
image 354) in which steep changes are smoothed based on the luminance model (e.g.,
luminance model 351).
[0100] Removal of surface-reflected light and high-frequency components of the captured
image of the palm is not limited to both the removal of surface-reflected light and
the removal of high-frequency components, but either one of which may be performed.
In addition, removal of surface-reflected light and high-frequency components of the
captured image of the palm may be performed only for a predetermined ratio without
being limited to removal of the whole. In addition, the ratio of surface-reflected
light and high-frequency components to be removed from the captured image of the palm
may be determined individually for the removal of surface-reflected light from the
captured image of the palm, and the removal of high-frequency components from the
captured image of the palm. In addition, the ratio of surface-reflected light and
high-frequency components to be removed from the captured image of the palm may be
preliminarily set, or may be set according to a predetermined condition (e.g., for
each type of each unit of image sensor provided in the authentication apparatus).
[Step S106] The surface information correcting unit 211a generates a luminance corrected
image (e.g., luminance corrected image 355) having uniformized the surface luminance
of the smoothed image (e.g., smoothed image 354), and terminates the surface information
correcting procedure. The surface information correcting unit 211a smooths the steep
change of luminance in the smoothed image, and uniformizes the surface luminance of
the smoothed image based on the luminance model, in order to facilitate extraction
of biometric information. For example, uniformization of surface luminance of the
smoothed image may be performed by reducing the luminance by a predetermined amount
or a predetermined ratio, based on the difference between the luminance model and
the smoothed image.
[0101] Next, a palm luminance model generating procedure performed at step S102 of the surface
information correcting procedure will be described. The luminance model generating
procedure is performed by the surface information correcting unit 211a.
[Step S111] The surface information correcting unit 211a reduces the amount of information
of the captured image by performing sampling of the captured image of the palm with
a lowered sampling frequency (down-sampling). In other words, the surface information
correcting unit 211a generates a first converted image from the captured image of
the palm. The sampling frequency may be preliminarily set, or may be determined according
to frequency components included in the captured image.
[Step S112] The surface information correcting unit 211a masks the palm part of the
first converted image, and fills (padding) an unmasked region which is not a part
of the palm (background part) with the average value of luminance of the unmasked
region. In other words, the surface information correcting unit 211a generates a second
converted image from the first converted image.
[Step S113] The surface information correcting unit 211a removes, from the second
converted image, the steep change of luminance by smoothing (smoothing spline) based
on a spline function. In other words, the surface information correcting unit 211a
generates a third converted image from the second converted image.
[Step S114] The surface information correcting unit 211a increases the amount of information
of the third converted image to generate a luminance model by performing sampling
of the third converted image with an increased sampling frequency (up-sampling). In
other words, the surface information correcting unit 211a generates a luminance model
(fourth converted image) from the third converted image.
[0102] Accordingly, the surface information correcting unit 211a may generate a luminance
model of the palm from the captured image of the palm. The surface information correcting
unit 211a then may remove surface-reflected light and high-frequency components from
the captured image of the palm. Furthermore, the surface information correcting unit
211a may generate a luminance corrected image having uniformized the surface luminance
of the image (smoothed image) having surface-reflected light and high-frequency components
removed therefrom.
[0103] Generation of the luminance corrected image from the captured image of the palm thus
performed by the surface information correcting unit 211a will be described using
graphs illustrated in FIG. 31. The graphs illustrated in parts (1) and (2) of FIG.
31 are graphs when the captured image of the palm is scanned in the lateral direction,
with the x-axis representing the position of the lateral direction of the palm and
the y-axis representing the luminance.
[0104] The surface information correcting unit 211a obtains a captured image representing
a luminance distribution such as that of the luminance graph 356. The luminance graph
356 is a graph schematically representing the luminance distribution when the palm
image 350 is scanned in the lateral direction. The luminance graph 356 indicates that
the luminance increases along the contour of the palm, with the luminance being lower
in the background part. In addition, the luminance graph 356 includes a part where
the luminance steeply changes due to specular reflection (specular reflection part),
a vein part where the luminance is lower than the periphery, and a high-frequency
component which becomes noise.
[0105] The surface information correcting unit 211a obtains a luminance model representing
the luminance distribution such as that of the luminance graph 357, by performing
the palm model generating procedure from the luminance graph 356 (part (1) of FIG.
31). The luminance graph 357 is a graph schematically representing the luminance distribution
when the luminance model 351 is scanned in the lateral direction. The luminance graph
357 has the specular reflection part, the vein part, and the high-frequency component
removed therefrom, which exist in the luminance graph 356.
[0106] The surface-reflected light removed by the surface information correcting unit 211a
is a specular reflection part in the luminance graph 356, corresponding to the surface-reflected
light 352, for example. The vein removed by the surface information correcting unit
211a is the vein part in the luminance graph 356. The high-frequency component removed
by the surface information correcting unit 211a corresponds to the high-frequency
component 353, for example.
[0107] The surface information correcting unit 211a obtains a smoothed image representing
a luminance distribution such as that of the luminance graph 358 by removing surface-reflected
light and high-frequency components from the luminance graph 356 and smoothing the
steep change based on the luminance model (part (2) of FIG. 31). The luminance graph
358 is a graph schematically representing the luminance distribution when the smoothed
image 354 is scanned in the lateral direction. The luminance graph 358 has the specular
reflection part and high-frequency components removed therefrom, which exist in the
luminance graph 356.
[0108] The surface information correcting unit 211a uniformizes the surface luminance of
the luminance graph 358, and obtains a luminance corrected image representing a luminance
distribution such as that of the luminance graph 359 (part (2) of FIG. 31). The luminance
graph 359 is a graph schematically representing the luminance distribution when the
luminance corrected image 355 is scanned in the lateral direction. In the luminance
graph 359, the gradient of the luminance existing in the luminance graph 358 is uniformized.
[0109] In this manner, the authentication apparatus 20a is able to obtain the luminance
corrected image, facilitating extraction of biometric information. In addition, the
authentication apparatus 20a is able to extend the tolerance of the posture of the
living body, since extraction of biometric information is facilitated. In addition,
the authentication apparatus 20a is able to identify surface-reflected light using
only gray scale images as the input, and thus it is possible to realize a higher processing
speed than when performing identification of surface-reflected light using color images.
[0110] Although it is common to use a low pass filter to remove high-frequency components,
a low pass filter, which works on the entire input image, is not suitable for removing
local high-frequency components. On the other hand, the authentication apparatus 20a
is able to successfully remove high-frequency components included in surface-reflected
light.
[0111] The noise of high-frequency components may be due to the sensitivity characteristics
inherent to the imaging device. For example, the authentication system 10 illustrated
in FIG. 2 has the authentication apparatus 20, the authentication apparatus 30, and
the authentication apparatus 40, each apparatus being provided with an imaging device
for photographing the living body and naturally having inherent sensitivity characteristics.
Alternatively, for example, there may be a case where different imaging devices are
used such that the authentication apparatus 20 has a CMOS image sensor as an imaging
device and the authentication apparatus 30 has a CCD image sensor as an imaging device.
[0112] Also in such case, the authentication apparatus 20a is able to remove noise due to
sensitivity characteristics inherent to the imaging device and extract stable biometric
information (vein characteristics). Accordingly, the authentication apparatus 20a
is able to maintain a high authentication precision even when different authentication
apparatuses are used for registering and matching biometric information. The authentication
system configured to include the authentication apparatus 20a is able to improve compatibility
and interoperability between different authentication apparatuses.
[0113] The processing function described above may be realized using a computer. In such
a case, a program is provided containing description of the functions supposed to
be realized by the authentication apparatus 20, the authentication apparatus 30, the
authentication apparatus 40, the authentication server 50, and the authentication
apparatus 20a. Executing the program by a computer realizes the above-mentioned processing
functions on the computer. The program containing description of the procedure may
be stored in computer-readable recording media (including portable recording media).
As computer-readable recording media, there are magnetic recording apparatus, optical
disks, magneto-optical recording media, semiconductor memories, and the like. As magnetic
recording apparatuses, there are Hard Disk Drives (HDD), flexible disks (FD), magnetic
tapes, and the like. As optical disks, there are DVD (Digital Versatile Disc), DVD-RAM,
CD-ROM, CD-R (Recordable)/RW (ReWritable), and the like. As magneto-optical recording
media, there are MO (Magneto-Optical disk) and the like.
[0114] When distributing a program, portable recording media such as DVD or CD-ROM having
the program stored thereon are sold, for example. Alternatively, a program may be
stored in a storage unit of a server computer, and transferred from the server computer
to other computers via a network.
[0115] A computer supposed to execute a program stores the program stored in a portable
storage medium or transferred from the server computer in its own storage unit. The
computer then reads the program from its own storage unit and performs a procedure
according to the program. The computer is also able to directly read the program from
the portable storage medium and perform a procedure according to the program. In addition,
the computer is also able to sequentially perform, each time a program is transferred
from the server computer, a procedure according to the program received.
[0116] Although a palm is exemplified as the living body surface in the embodiment described
above, it is not limiting, and any part may be used as long as it is a living body
surface.
[0117] For example, the living body surface may be a sole, a finger of a hand or a foot,
a dorsum of a hand or a foot, a wrist, an arm, or the like.
[0118] When using a vein for authentication, it suffices that the living body surface is
a part where the vein is observable.
[0119] A living body surface allowing identification of a biometric information acquisition
site is advantageous for authentication. For example, a palm or a face allows identification
of a site from the obtained image.
[0120] Biometric information used for authentication is not limited to a vein and may be
a fingerprint, a palm print, or the like.
[0121] In addition, various changes may be made to the embodiments described above within
a range that does not depart from the scope of the embodiments.
[0122] The above-described embodiments illustrate merely a principle of the present invention.
Further, various modifications and alterations may be made by those skilled in the
art, the present invention is not intended to be limited to the above-described precise
configurations and application examples, and it should be understood that all corresponding
variations and equivalents thereof fall within a scope of the present invention by
the appended claims and equivalents thereof.
Reference Signs List
[0123]
1 authentication apparatus
2 surface information extraction unit
3 surface information analysis unit
4 surface information correcting unit
5 authentication unit
10 authentication system
20, 30, 40, 20a authentication apparatus
21 processing apparatus
22 display
23 keyboard
24 sensor-unit-embedded mouse
24a, 31, 43 sensor unit
24b control unit
24c image capturing unit
24d distance measuring unit
24e storage unit
24f communication unit
25, 42 IC card reader/writer
26 IC card
41 numerical keypad
44 door
50 authentication server
51 network
52 unaccepted biometric information database
53 unaccepted environment information database
54 guidance information database
60 hand
61, 68 entire palm region
62, 69 subregion
63, 70 finer subregion
101 CPU
102 RAM
103 HDD
104 communication interface
105 graphic processing unit
106 input/output interface
107 bus
110 portable storage medium
200 control unit
201 storage unit
202 notification unit
203 communication unit
204 image input unit
205 object extraction unit
206 palm determination unit
207 palm clipping unit
208 contour correcting unit
209 surface information extraction unit
210 surface information analysis unit
211, 211a surface information correcting unit
212 unaccepted information acquisition unit
213 guidance method selecting unit
214 biometric information extraction unit
215 matching unit